Genotype imputation from low-coverage data for medical and population genetic analyses.

ABSTRACT: Genotype imputation from low-pass sequencing data presents unique opportunities for genomic analyses but comes with specific challenges. In this study, we explore the impact of quality filters on genetic ancestry and Polygenic Score (PGS) estimation after imputing 32,769 low-pass genome-wide sequences (LPS) from noninvasive prenatal screening (NIPS) with an average autosomal sequence depth of ∼0.15×. In studies involving ultra-low coverage sequences, conventional approaches to secure genotype accuracy may fail, especially when multiple samples are pooled. To enhance the proportion of high-quality genotypes in large data sets, we introduce a filtering approach called GDI that combines genotype probability (GP), alternate allele dosage (DS), and INFO score filters. We demonstrate that the im

SUBMITTER: Biagini SA 

PROVIDER: S-EPMC12400947 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature